def test_transition_multiple(self):
sm = StateMachineNetwork(
[State(1), State(2)],
[Transition(1, 2), Transition(2, 1)])
self.assertEqual(len(sm.transitions), 2)
self.assertEqual(len(sm.transitions[1]), 1)
self.assertEqual(len(sm.transitions[2]), 1)
def test_execution_true_transition(self):
sm = StateMachineNetwork([State(1), State(2)], [Transition(1, 2)])
sm.states[1].set_biases([1, 2])
sm.states[1].set_weights([[1, 2], [3, 4]])
sm.transitions[1][0].add_condition(Condition(0, operator.eq, 5))
next_state, output = sm.activate(1, [5, 10])
self.assertEqual(next_state, 2)
self.assertEqual(output, [26, 57])
def test_execution_multiple_transitions_all_false(self):
sm = StateMachineNetwork(
[State(1), State(2), State(3)],
[Transition(1, 2), Transition(1, 2)])
sm.states[1].set_biases([1, 2])
sm.states[1].set_weights([[1, 2], [3, 4]])
sm.transitions[1][0].add_condition(Condition(0, operator.eq, 4))
sm.transitions[1][1].add_condition(Condition(1, operator.gt, 10))
next_state, output = sm.activate(1, [5, 10])
self.assertEqual(1, next_state)
self.assertEqual(output, [26, 57])
def test_execution_no_transitions(self):
sm = StateMachineNetwork([State(1)], [])
sm.states[1].set_biases([1, 2])
sm.states[1].set_weights([[1, 2], [3, 4]])
next_state, output = sm.activate(1, [5, 10])
self.assertEqual(next_state, 1)
self.assertEqual(output, [26, 57])
def compare_state_outcomes(genome, sensor_input_file):
# This function evaluates the difference of the states by running it on a randomly generated set
# input values and reporting the distance between the output vectors of the states.
# Load the randomly generated sensor inputs
with open(sensor_input_file, 'r') as csv_file:
csv_reader = csv.reader(csv_file, quoting=csv.QUOTE_NONNUMERIC)
sensor_vectors = [row for row in csv_reader]
# Evaluate the sensor inputs on each genome.
state_differences = dict()
activations = ActivationFunctionSet()
aggregations = AggregationFunctionSet()
for enc_state1 in itervalues(genome.states):
state1 = State(1, enc_state1.weights, enc_state1.biases,
aggregations.get(enc_state1.aggregation),
activations.get(enc_state1.activation))
for enc_state2 in itervalues(genome.states):
key_pair = (enc_state1.key, enc_state2.key)
if key_pair[0] != key_pair[1] and key_pair not in state_differences \
and key_pair[::-1] not in state_differences:
state2 = State(2, enc_state2.weights, enc_state2.biases,
aggregations.get(enc_state2.aggregation),
activations.get(enc_state2.activation))
output_pairs = [(state1.activate(inputs),
state2.activate(inputs))
for inputs in sensor_vectors]
distances = [
np.average(
np.abs(
np.array(output_pair[0]) -
np.array(output_pair[1])))
for output_pair in output_pairs
]
state_differences[key_pair] = np.average(distances), np.std(
distances)
return state_differences
def test_2_in_1_out(self):
state = State(42)
state.set_biases([0])
state.set_weights([[2, 3]])
self.assertListEqual(state.activate([5, 10]), [40])
def test_init(self):
state = State(42)
self.assertEqual(state.id, 42)
self.assertIsNone(state.biases)
self.assertIsNone(state.weights)
def test_add_state(self):
sm = StateMachineNetwork([State(1)], [])
self.assertEqual(len(sm.states), 1)
self.assertEqual(sm.states[1].id, 1)
def test_transition_multiple_begin_state(self):
sm = StateMachineNetwork(
[State(1), State(2), State(3)],
[Transition(1, 2), Transition(1, 3)])
self.assertEqual(len(sm.transitions), 3)
self.assertEqual(len(sm.transitions[1]), 2)
def test_invalid_transition(self):
self.assertRaises(ValueError, StateMachineNetwork, [State(1)],
[Transition(4, 2)])
def test_1_in_1_out(self):
state = State(42)
state.set_biases([1])
state.set_weights([[2]])
self.assertListEqual(state.activate([5]), [11])
def test_not_without_weights(self):
state = State(42)
state.set_biases([2, 3])
self.assertRaises(AssertionError, state.activate, [5, 10])
def test_2_in_3_out(self):
state = State(42)
state.set_biases([0, 1, 2])
state.set_weights([[2, 3], [4, 5], [1, 2]])
self.assertListEqual(state.activate([5, 10]), [40, 71, 27])
def test_3_in_2_out(self):
state = State(42)
state.set_biases([0, 1])
state.set_weights([[2, 3, 1], [4, 5, 1]])
self.assertListEqual(state.activate([5, 10, 20]), [60, 91])
def test_invalid_state(self):
sm = StateMachineNetwork([State(1)], [])
self.assertRaises(KeyError, sm.activate, 3, [5, 10])
def test_to_little_weight_length(self):
state = State(42)
state.set_biases([2, 3])
state.set_weights([[2], [2]])
self.assertRaises(AssertionError, state.activate, [5, 2])
def test_to_many_weight_length(self):
state = State(42)
state.set_biases([2, 2])
state.set_weights([[2, 3, 3], [3, 4, 5]])
self.assertRaises(AssertionError, state.activate, [5, 10])
def test_add_state_twice(self):
with self.assertRaises(ValueError) as context:
StateMachineNetwork([State(1), State(1)], [])
self.assertTrue('State included twice' in str(context.exception))
def test_too_short_bias_length(self):
state = State(42)
state.set_biases([2])
state.set_weights([[2, 3], [4, 5]])
self.assertRaises(AssertionError, state.activate, [5, 10])
